Uplink measurements for wireless systems

ABSTRACT

A method for measuring channel quality in a wireless transceiver is disclosed, comprising: receiving, at a wireless transceiver, an analog signal from a user equipment (UE); converting the analog signal to a plurality of digital samples at an analog to digital converter (ADC); performing a fast Fourier transform (FFT) on the plurality of digital samples to generate frequency domain samples; identifying an uplink demodulation reference signal (DMRS) symbol; performing channel estimation on the DMRS symbol to identify an estimate of channels; creating a noise covariance matrix from the estimate of channels; and deriving an interference measure from the noise covariance matrix.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims the benefit ofpriority under 35 U.S.C. § 120 of, U.S. patent application Ser. No.15/484,121, titled “Uplink Measurements for Wireless Systems,” havingattorney docket no. PWS-71868US01, and filed Apr. 10, 2017, which itselfclaims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional PatentApplication No. 62/320,472, having attorney docket no. PWS-71869U500,filed Apr. 9, 2016, and entitled “Uplink Measurements for LTE 4GSystems,” each of which is hereby incorporated by reference in itsentirety for all purposes. Additionally, U.S. Pat. App. Pub. Nos.US20140086120, US20140092765, US20140133456, US20150045063, andUS20150078167 are hereby incorporated by reference in their entirety forall purposes.

BACKGROUND

In LTE 4G systems, uplink measurements such as Interference per ResourceBlock (RB), Noise per RB, Thermal Noise power and Interference Powerhold significant value for the performance of the overall uplink systembehavior. These measurement values are calibrated and passed over tohigher layers, which can assist with the scheduling of RB's andmodulation rate etc. These values also assist the major decision takingssuch as for inter cell interference co-ordination (ICIC), handover etc.

In Long Term Evolution (LTE/LTE-A), physical uplink shared channel(PUSCH) is used to transmit the uplink data from UE (user equipment)along with control information. PUSCH uses DMRS to help the receiver toestimate channel and equalize the received data. The DMRS also has amajor significance in terms of deriving various major measurements. Thesignificance of the measurement values is to assist with the schedulingof the RB in order to enhance the user data decoding and the overallsystem performance.

SUMMARY

Systems and methods for uplink measurements in wireless systems aredisclosed.

In one embodiment, a method for measuring channel quality in a Long TermEvolution (LTE) transceiver is disclosed, comprising: receiving, at aLong Term Evolution (LTE) wireless transceiver, an analog signal from auser equipment (UE); converting the analog signal to a plurality ofdigital samples at an analog to digital converter (ADC); performing afast Fourier transform (FFT) on the plurality of digital samples togenerate frequency domain samples; identifying an uplink demodulationreference signal (DMRS) symbol; performing channel estimation on theDMRS symbol to identify an estimate of channels; creating a noisecovariance matrix from the estimate of channels; and deriving aninterference measure from the noise covariance matrix.

The LTE wireless transceiver may be an LTE or LTE-A eNodeB, and theanalog signal may be a physical uplink shared channel (PUSCH). Theinterference measure may be one of: interference per resource block;noise per resource block; thermal noise power; interference power; noiseplus interference per resource block; or noise power per resource block.The interference measure may be interference per resource block, derivedaccording to the equation found herein. The interference measure may benoise plus interference per resource block, derived according to theequation found herein. The method may further comprise performing intercell interference coordination with a second wireless transceiver usingthe interference measure. The method may further comprise adjusting ahandover threshold based on the interference measure. The method mayfurther comprise transmitting the interference measure to a coordinationserver in an operator core network and receiving a configurationinstruction from the coordination server based on the interferencemeasure. The method may further comprise scheduling data transmissionsbased on the interference measure. The method may further comprisesending the interference measure to a scheduler. The method may furthercomprise setting a modulation control scheme (MCS) for the UE based onthe interference measure.

In another embodiment, an uplink receiver for a wireless base station isdisclosed, comprising: an analog to digital conversion module, forconverting a received analog signal to a plurality of digital samples; afast Fourier transform (FFT) module for performing FFT on the pluralityof digital samples to generate frequency domain samples; an uplinkdemodulation reference signal (DMRS) identification module foridentifying a DMRS symbol from the frequency domain samples; and anuplink signal strength measurement module, coupled to the uplink DMRSidentification module, configured to perform channel estimation on theDMRS symbol to identify an estimate of channels, create a noisecovariance matrix from the estimate of channels, and derive aninterference measure from the noise covariance matrix.

The wireless base station may be an eNodeB, and the analog signal may bea physical uplink shared channel (PUSCH) received from a user equipment(UE). The interference measure may be one of: interference per resourceblock; noise per resource block; thermal noise power; interferencepower; noise plus interference per resource block; or noise power perresource block. The interference measure may be interference perresource block, derived according to the equation found herein. Theinterference measure may be noise plus interference per resource block,derived according to the equation found herein. The uplink receiver maybe further configured to perform inter cell interference coordinationwith a second wireless transceiver using the interference measure. Theuplink receiver may be further configured to adjust a handover thresholdbased on the interference measure. The uplink receiver may be furtherconfigured to schedule data transmissions based on the interferencemeasure. The uplink receiver may be further configured to send theinterference measure to a scheduler. The uplink receiver may be furtherconfigured to set a modulation control scheme (MCS) for the UE based onthe interference measure. The uplink receiver may further comprise aself-organizing network (SON) module in communication with acoordination server in an operator core network, the SON moduleconfigured to transmit the interference module to the coordinationserver.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of an uplink subframe, in accordance withsome embodiments.

FIG. 2 is a schematic diagram of an uplink receiver block for performingmeasurements, in accordance with some embodiments.

FIG. 3 is a schematic diagram of an enhanced base station, in accordancewith some embodiments.

DETAILED DESCRIPTION

This disclosure focuses on the computation of certain measurement valuesderived from the uplink demodulation reference signal (DMRS) via thecomputation of a noise covariance matrix. We derive the expressions forthe measurements considering a two-antenna system. A description of theuplink sub-frame along with a block level diagram, and a basic systemmodule of a 4G LTE system in accordance with some embodiments, areprovided. Uplink measurements and their derivation and computation aredisclosed. The paper mainly focuses on the derivation and computation ofthe following measurements: Channel Estimation Computation; NoiseCovariance Matrix Computation; Noise per RB; Interference per RB;Thermal Noise Power; System Model; and Uplink sub-frame.

The measurements computed in this paper have been supported over PSC913x processors for baseband LTE Pico/Femto systems. The measurementresults are taken by FAPI and sent to L2 in the vendor-specific part ofthe SUBFRAME.indication message, in the following structure. The resultsshow a relatively accurate computations using the equations provided inthis paper.

The following references are incorporated herein in their entirety forall purposes: Saurabh Shandilya, Ajay Sharma, Gopikrishna CharipadiDigital Networking, Freescale Semiconductor. Noida, Noida, India: A LowComplexity SINR Computation for 4G Data Channel In: IEEE ICACCS 2015 5-7Jan. (2015); Wang, Y., Zheng, A., Zhang, J., Yang, D.: A Novel ChannelEstimation Algorithm for Sounding Reference Signal in LTE uplinkTransmission. In: IEEE Conference on Communications Technology andApplications, December 7, pp. 412-415 (2009); Hou, X., Zhang, Z.,Kayama, H.: DMRS Design and Channel Estimation for LTE Advanced MIMOuplink, July 25 (2010); S Sesia, I Toufik, M Baker. LTE the UMTS LongTerm Evolution; 3GPP TS 36.141: Evolved Universal Terrestrial RadioAccess (E-UTRA); Base Station (BS) conformance testing, V10.10.0(2013-03), Section 6.5.1.

FIG. 1 is a schematic diagram of an LTE uplink subframe, in accordancewith some embodiments. A single radio frame 101 is 10 msec in duration.A single uplink sub-frame of 1 msec 102 includes two slots of 0.5 mseceach, 103 and 104. Each slot contains 7 OFDM symbols 104 a-104 g in thecase of normal cyclic prefix, or 6 OFDM symbols in the case of extendedcyclic prefix. Considering the case of normal cyclic prefix in FIG. 1,the DMRS OFDM symbol 104 d is placed at the 4th OFDM symbol of everyslot. OFDM symbols 104 a, 104 b, 104 c, 104 e, 104 f, 104 g are mainlyconsidered as the Data OFDM symbols of each slot. DMRS for PUSCH in thefrequency domain will be mapped to the same set of physical resourceblocks (PRB) used for the corresponding physical uplink shared channel(PUSCH) transmission with the same length expressed by the number ofsub-carriers. DMRS utilizes Zadoff-Chu sequence as the bases forreference signal generation. Zadoff-Chu possess a unique property thatits cyclic shifted versions of its own sequence are consideredorthogonal to one another. Besides this Zadoff-Chu also contains thefollowing useful properties: it has constant amplitude; it has zerocircular auto correlation; it has flat frequency domain response; thecircular cross-correlation between two Zadoff-Chu sequences is low; andit has constant amplitude provided that the root sequence is a primenumber.

FIG. 2 is a schematic DIAGRAM of an uplink receiver block for performingmeasurements, in accordance with some embodiments. A simplified uplinkreceiver block of a LTE system capturing the measurement block is shownin FIG. 2. The block schematically shows the processing entities, whichmay be implemented as software or hardware modules. ADC (Analogue toDigital Convertor) 201 captures the samples and processes them intodigital level. The samples are then passed to the FFT (Fast FourierTransform) 202. The FFT transforms the signal from its original domain,being the time domain, into the frequency domain. The processing fromADC to FFT happens on the OFDM symbol bases. Once the DMRS OFDM symbolhas been processed via the ADC to the FFT it is passed down to the DMRSsignal processing block 203. Identification of the DMRS symbol may beperformed within the DMRS signal processing block 203, in someembodiments. Once the DMRS symbol is identified, it is passed toprocessing block 204.

The signal processing block 204 first computes the channel estimates viathe channel estimate at block 205. Next, the noise covariance matrix iscomputed at block 206 from the channel estimates as explained in sectionIII. The Noise covariance matrix is then utilized to derive severalmeasurements at block 207.

Although there are many ways to compute the measurements valuesdescribed herein, we explain how Noise Covariance Matrix is computed viathe Channel Estimates and correspondingly how each measurement values isderived. The measurements are all based on the Noise Covariance Matrixcomputed per RB. The computation of Noise Covariance Matrix is performedvia the channel estimates which is obtained from the DMRS signal afterthe FFT as seen in FIG. 2 on OFDM symbols no 4 of each slot per subframe.

Channel Estimations Computation

A raw channel estimate is first computed as the product of the receivedsamples after FFT and the conjugate of the DMRS sequence. The DMRSsequence is used as a known sequence to create a matched filter. (Theprinciples described herein could be used in conjunction with anotherradio access technology or modulation technology, such as a 3G WCDMAsignal, using the principle of using a known signal to generate amatched filter, in the way that a received LTE signal herein ismultiplied with the conjugate of the DMRS sequence, to generate acorrelation receiver that integrates energy received in that period.)

h _(raw) ^(a,s,sc) =y _(dmrs ofdm symbol) ^(a,s,sc)*DMRS ^(s,sc)

The parameters here are:

-   -   a,s,sc    -   y_(dmrs ofdm symbol) ^(a,s,sc): Received sample after FFT    -   DMRS ^(s,sc): DMRS sequence    -   a: antenna    -   s: slot    -   sc: subcarrier

Then for each subcarrier, the raw channel estimate is filtered with thechannel estimate from surrounding subcarriers. The purpose of filteringis to improve channel estimate accuracy by filtering out the noise.

$h^{a,s,{sc}} = {\frac{1}{L}{\sum\limits_{i = 0}^{L - 1}\; {c_{i}*h_{raw}^{a,s,{{sc} - \frac{L - 1}{2} + i}}}}}$

The parameters here are:

h^(a,s,sc: Actual Channel Estimates)h_(raw) ^(a,s,sc): Raw Channel Estimatesc_(t): filter tapL: number of filter tapsa: antennas: slotsc: subcarrier

Noise Covariance Matrix Computation

The noise is computed as the difference between the final channelestimate and the raw channel estimate:

N ^(a,s,sc) =h ^(a,s,sc) −h _(raw) ^(a,s,sc)

Cn _(i,j) ^(s,p)= 1/12Σ_(ac=12p) ^(12p+11) N ^(i,s,sc) *N ^(j,s,sc)

Cn: Noise Covariance Matrix

i & j: RX antenna indicesp: Physical Resource Block index.

The noise covariance per RB computed is as below:

${Cn} = \begin{pmatrix}C_{1,1} & C_{1,2} \\C_{2,1} & C_{2,2}\end{pmatrix}$

C_(1,1): Noise+Interference for anti

C _(1,1) =|h ₁|² I+N  eq 1

C_(1,2): Intereference

C_(2,1): Intereference conjugate of C_(1,2)

C_(2,2): Noise+Interference for ant 2

C _(2,2) =|h ₂|² I+N  eq 2

Received Total RB Power (RTRP)

Received Signal Strength Indicator (RSSI) is the average of I²+Q² on FFToutput of DMRS OFDM symbol of the DMRS OFDM symbol.

Example 1

Considering 1 RB allocation for a user for a two antenna system the RSSIis the average over the Diagonal element of the Noise Covariance Matrixover DMRS symbols computed.

${Cn} = \begin{pmatrix}C_{1,1} & C_{1,2} \\C_{2,1} & C_{2,2}\end{pmatrix}$${RSSI} = {\frac{1}{2}\left\lbrack {C_{1,1} + C_{2,2}} \right\rbrack}$

Example 2

Considering 10 RB allocation for a user for a two antenna system theRSSI is the average over the Diagonal element of the Noise CovarianceMatrix over DMRS symbols computed.

$\mspace{76mu} {{Cn} = {\frac{1}{10}*\frac{1}{2}{\sum\limits_{{RB} = 1}^{10}\; \begin{pmatrix}C_{1,1} & C_{1,2} \\C_{2,1} & C_{2,2}\end{pmatrix}}}}$${RSSI} = {\frac{1}{2}*\frac{1}{10}\left( {\left\lbrack {C_{1,1} + C_{2,2}} \right\rbrack_{{RB}\; 1} + {\left\lbrack {C_{1,1} + C_{2,2}} \right\rbrack_{{RB}\; 2}\mspace{14mu} \ldots \mspace{14mu} {\ldots \mspace{14mu}\left\lbrack {C_{1,1} + C_{2,2}} \right\rbrack}_{{RB}\; 10}}} \right)}$

Thermal Noise Power

Step 1: Interference is computed as the off diagonal power of the noisecovariance matrix.

Interference per RB is:

${{IP}(p)} = {\frac{1}{N_{{off}\_ {diag}}*N_{slot}}{\sum\limits_{o = 1}^{{Noff}\_ {diag}}\; {\sum\limits_{t = 1}^{Nslot}\; {C_{o,{t.p}}}}}}$

The parameters here are:

C_(o,t.p): Noise covariance matrix off-diagonal.

Noff_diag: Number of off-diagonal elements in the noise covariancematrix.

Nslot: Number of slots over which the average is done.

Step 2: Received interference power is Noise+Interference per RB. ForPUSCH allocations, it is computed in RSP as the average over theDiagonal element of the Noise Covariance Matrix.

Noise+Interference per RB is:

${{NIP}(p)} = {\frac{1}{N_{diag}*N_{slot}}{\sum\limits_{d = 1}^{Ndiag}\; {\sum\limits_{t = 1}^{Nslot}\; {C_{d,{t.p}}}}}}$

The parameters here are:

c_(d,t.p): Noise Covariance Matrix diagonalNdiag: Number of diagonal elements in the Noise Covariance MatrixNslot: Number of slots over which the average is done

Step 3: Noise power per RB is computed as the difference betweennoise+interference and interference.

Noise power per RB is:

NP(p)=NIP(p)−IP(p)

Step 4: Thermal noise power is computed as the sum of noise per RB, overall RBs. Thermal noise power:

No=Σ _(n=1) ^(nu) ^(_) ^(RB) NP(n)

Exemplary Hardware

FIG. 3 is a schematic diagram of an enhanced eNodeB, in accordance withsome embodiments. Enhanced eNodeB 300 may include processor 302,processor memory 304 in communication with the processor, basebandprocessor 306, and baseband processor memory 308 in communication withthe baseband processor. Enhanced eNodeB 300 may also include first radiotransceiver 310 and second radio transceiver 312, internal universalserial bus (USB) port 316, and subscriber information module card (SIMcard) 318 coupled to USB port 314. In some embodiments, the second radiotransceiver 312 itself may be coupled to USB port 316, andcommunications from the baseband processor may be passed through USBport 316.

A self-organizing network (SON) module 330 may also be included, whichmay include a database (not shown), in some embodiments, or which may bein communication with a coordination server (not shown), in someembodiments, or both, in some embodiments. The channel estimations andchannel quality measurements, the noise covariance matrices, the noiseper RB or channel for any given RB or channel, or any other calculatedor received parameters described herein, may be sent via the SON moduleto the coordination server and used for coordinating transmissionsthroughout the network at multiple base stations, in some embodiments.

Processor 302 and baseband processor 306 are in communication with oneanother. Processor 302 may perform routing functions, and may determineif/when a switch in network configuration is needed. Baseband processor306 may generate and receive radio signals for both radio transceivers310 and 312, based on instructions from processor 302. In someembodiments, processors 302 and 306 may be on the same physical logicboard. In other embodiments, they may be on separate logic boards.

The first radio transceiver 310 may be a radio transceiver capable ofproviding LTE eNodeB functionality, and may be capable of higher powerand multi-channel OFDMA. The second radio transceiver 312 may be a radiotransceiver capable of providing LTE UE functionality. Both transceivers310 and 312 are capable of receiving and transmitting on one or more LTEbands. In some embodiments, either or both of transceivers 310 and 312may be capable of providing both LTE eNodeB and LTE UE functionality.Transceiver 310 may be coupled to processor 302 via a PeripheralComponent Interconnect-Express (PCI-E) bus, and/or via a daughtercard.Transceiver 310 may have its L1 (PHY), L2 (MAC), and other layersimplemented using software modules that are configured to run onprocessor 302, as described herein.

Transceiver 312 may be for providing LTE UE functionality, in effectemulating a user equipment, it may be connected via the same ordifferent PCI-E bus, or by a USB bus, and may also be coupled to SIMcard 318. SIM card 318 may provide information required forauthenticating the simulated UE to the evolved packet core (EPC). Whenno access to an operator EPC is available, a local EPC on the enhancedeNodeB itself (not shown) may be used, or another local EPC on thenetwork may be used. This information may be stored within the SIM card,and may include one or more of an international mobile equipmentidentity (IMEI), international mobile subscriber identity (IMSI), orother parameter needed to identify a UE. Special parameters may also bestored in the SIM card or provided by the processor during processing toidentify to a target eNodeB that device 300 is not an ordinary UE butinstead is a special UE for providing backhaul to device 300.

Alternatively, transceiver 312 may be another radio access technology(RAT) radio, such as a 2G, 3G, 3G, 5G, or Wi-Fi radio. Transceivers 310and 312 may have different RATs or the same RAT. As each RAT and as eachradio has its own PHY, the concepts and methods described herein couldbe used for 2G, 3G, 3G, 5G, or Wi-Fi PHY and MAC layer error messaging,or a combination of multiple RAT layer error messaging modules.

Wired backhaul or wireless backhaul may be used. Wired backhaul may bean Ethernet-based backhaul (including Gigabit Ethernet), or afiber-optic backhaul connection, or a cable-based backhaul connection,in some embodiments. Additionally, wireless backhaul may be provided inaddition to wireless transceivers 310 and 312, which may be Wi-Fi802.11a/b/g/n/ac/ad/ah, Bluetooth, ZigBee, microwave (includingline-of-sight microwave), or another wireless backhaul connection. Anyof the wired and wireless connections may be used for either access orbackhaul, according to identified network conditions and needs, and maybe under the control of processor 302 for reconfiguration.

Other elements and/or modules may also be included, such as a homeeNodeB, a local gateway (LGW), or another module. Additional radioamplifiers, radio transceivers and/or wired network connections may alsobe included.

Processor 302 may identify the appropriate network configuration, andmay perform routing of packets from one network interface to anotheraccordingly. Processor 302 may use memory 304, in particular to store arouting table to be used for routing packets. Baseband processor 306 mayperform operations to generate the radio frequency signals fortransmission or retransmission by both transceivers 310 and 312.Baseband processor 306 may also perform operations to decode signalsreceived by transceivers 310 and 312. Baseband processor 306 may usememory 308 to perform these tasks. In some embodiments, the stepsdescribed herein, including channel estimation and channel measurement,may be performed at the processor 302, or the baseband processor 306, ora combination of both. In some embodiments, the processor 302 mayreceive PHY samples from the baseband processor 306 and perform themajority of the steps herein, such as identifying resource blocks andOFDM symbols, and calculating noise covariance matrices.

In some embodiments, the radio transceivers described herein may be basestations compatible with a Long Term Evolution (LTE) radio transmissionprotocol or air interface. The LTE-compatible base stations may beeNodeBs. In addition to supporting the LTE protocol, the base stationsmay also support other air interfaces, such as UMTS/HSPA, CDMA/CDMA2000,GSM/EDGE, GPRS, EVDO, other 3G/2G, legacy TDD, or other air interfacesused for mobile telephony. In some embodiments, the base stationsdescribed herein may support Wi-Fi air interfaces, which may include oneor more of IEEE 802.11a/b/g/n/ac. In some embodiments, the base stationsdescribed herein may support IEEE 802.16 (WiMAX), to LTE transmissionsin unlicensed frequency bands (e.g., LTE-U, Licensed Access or LA-LTE),to LTE transmissions using dynamic spectrum access (DSA), to radiotransceivers for ZigBee, Bluetooth, or other radio frequency protocols,or other air interfaces. In some embodiments, the base stationsdescribed herein may use programmable frequency filters. In someembodiments, the base stations described herein may provide access toland mobile radio (LMR)-associated radio frequency bands. In someembodiments, the base stations described herein may also support morethan one of the above radio frequency protocols, and may also supporttransmit power adjustments for some or all of the radio frequencyprotocols supported. The embodiments disclosed herein can be used with avariety of protocols so long as there are contiguous frequencybands/channels. Although the methods described assume a single-in,single-output (SISO) system, the techniques described can also beextended to multiple-in, multiple-out (MIMO) systems.

In some embodiments, the methods described can be used with 2G, 3G, 3G,5G, Wi-Fi, or multi-RAT base stations or access points. In someembodiments, the methods described could be used in a UE as well asfemto, nodeB, eNodeB, metro, or macro, as long as an API is used forcommunication between the PHY and the MAC layers.

Those skilled in the art will recognize that multiple hardware andsoftware configurations could be used depending upon the accessprotocol, backhaul protocol, duplexing scheme, or operating frequencyband by adding or replacing daughtercards to the dynamic multi-RAT node.Presently, there are radio cards that can be used for the varying radioparameters. Accordingly, the multi-RAT nodes of the present inventioncould be designed to contain as many radio cards as desired given theradio parameters of heterogeneous mesh networks within which themulti-RAT node is likely to operate. Those of skill in the art willrecognize that, to the extent an off-the shelf radio card is notavailable to accomplish transmission/reception in a particular radioparameter, a radio card capable of performing, e.g., in white spacefrequencies, would not be difficult to design.

Those of skill in the art will also recognize that hardware may embodysoftware, software may be stored in hardware as firmware, and variousmodules and/or functions may be performed or provided either as hardwareor software depending on the specific needs of a particular embodiment.

In the present disclosure, the words location and position may be usedin various instances to have the same meaning, as is common in therelevant art.

In any of the scenarios described herein, where processing may beperformed at the cell, the processing may also be performed incoordination with a cloud coordination server. The eNodeB may be incommunication with the cloud coordination server via an X2 protocolconnection, or another connection. The eNodeB may perform inter-cellcoordination via the cloud communication server, when other cells are incommunication with the cloud coordination server. The eNodeB maycommunicate with the cloud coordination server to determine whether theUE has the ability to support a handover to Wi-Fi, e.g., in aheterogeneous network.

Although the methods above are described as separate embodiments, one ofskill in the art would understand that it would be possible anddesirable to combine several of the above methods into a singleembodiment, or to combine disparate methods into a single embodiment.For example, all of the above methods could be combined. In thescenarios where multiple embodiments are described, the methods could becombined in sequential order, in various orders as necessary.

Although the above systems and methods for providing interferencemitigation are described in reference to the Long Term Evolution (LTE)standard, one of skill in the art would understand that these systemsand methods could be adapted for use with other wireless standards orversions thereof. For example, while certain methods are understood toutilize FAPI, other methods and aspects do not require the LTE SmallCell Forum FAPI or any 3GPP Release.

In some embodiments, the software needed for implementing the methodsand procedures described herein may be implemented in a high levelprocedural or an object-oriented language such as C, C++, C#, Python, orJava. The software may also be implemented in assembly language ifdesired. Packet processing implemented in a network device can includeany processing determined by the context. For example, packet processingmay involve high-level data link control (HDLC) framing, headercompression, and/or encryption. In some embodiments, software that, whenexecuted, causes a device to perform the methods described herein may bestored on a computer-readable medium such as read-only memory (ROM),programmable-read-only memory (PROM), electrically erasableprogrammable-read-only memory (EEPROM), flash memory, or a magnetic diskthat is readable by a general or special purpose-processing unit toperform the processes described in this document. The processors caninclude any microprocessor (single or multiple core), system on chip(SoC), microcontroller, digital signal processor (DSP), graphicsprocessing unit (GPU), or any other integrated circuit capable ofprocessing instructions such as an x86 microprocessor.

Although the present disclosure has been described and illustrated inthe foregoing example embodiments, it is understood that the presentdisclosure has been made only by way of example, and that numerouschanges in the details of implementation of the disclosure may be madewithout departing from the spirit and scope of the disclosure, which islimited only by the claims which follow. Various components in thedevices described herein may be added, removed, or substituted withthose having the same or similar functionality. Various steps asdescribed in the figures and specification may be added or removed fromthe processes described herein, and the steps described may be performedin an alternative order, consistent with the spirit of the invention.Features of one embodiment may be used in another embodiment. Otherembodiments are within the following claims.

1. A method for measuring channel quality in a wireless transceiver,comprising: receiving, at a wireless transceiver, an analog signal froma user equipment (UE); converting the analog signal to a plurality ofdigital samples at an analog to digital converter (ADC); performing afast Fourier transform (FFT) on the plurality of digital samples togenerate frequency domain samples; identifying an uplink demodulationreference signal (DMRS) symbol; performing channel estimation on theDMRS symbol to identify an estimate of channels; creating a noisecovariance matrix from the estimate of channels; deriving aninterference measure from the noise covariance matrix; wherein theinterference measure comprises noise plus interference per resourceblock, derived as an average of summation of diagonal matrix elementsover a plurality of slots and a plurality of antennas, and wherein thediagonal matrix elements are noise plus interference components.
 2. Themethod of claim 1, wherein the wireless transceiver is an LTE or LTE-AeNodeB, and the analog signal is a physical uplink shared channel(PUSCH).
 3. The method of claim 1, wherein the interference measurefurther comprises one of: interference per resource block; noise perresource block; thermal noise power; interference power; noise plusinterference per resource block; or noise power per resource block. 4.The method of claim 1, further comprising obtaining a secondinterference measure that is interference per resource block, derivedaccording to an equation${{{IP}(p)} = {\frac{1}{N_{{off}\_ {diag}}*N_{slot}}{\sum\limits_{o = 1}^{{Noff}\_ {diag}}\; {\sum\limits_{t = 1}^{Nslot}\; {C_{o,{t.p}}}}}}},$where C_(o,t.p) is a noise covariance matrix off-diagonal; Noff_diag isa number of off-diagonal elements in a noise covariance matrix; andNslot is a number of slots over which an average is computed.
 5. Themethod of claim 1, wherein the interference measure is noise plusinterference per resource block, derived according to an equation${{{NIP}(p)} = {\frac{1}{N_{diag}*N_{slot}}{\sum\limits_{d = 1}^{Ndiag}\; {\sum\limits_{t = 1}^{Nslot}\; {C_{d,{t.p}}}}}}},$where C_(d,t.p) is a Noise Covariance Matrix diagonal; Ndiag is a numberof diagonal elements in the Noise Covariance Matrix; and Nslot is anumber of slots over which an average is performed.
 6. The method ofclaim 1, further comprising performing inter cell interferencecoordination with a second wireless transceiver using the interferencemeasure.
 7. The method of claim 1, further comprising adjusting ahandover threshold based on the interference measure.
 8. The method ofclaim 1, further comprising transmitting the interference measure to acoordination server in an operator core network and receiving aconfiguration instruction from the coordination server based on theinterference measure.
 9. The method of claim 1, further comprisingscheduling data transmissions based on the interference measure.
 10. Themethod of claim 1, further comprising sending the interference measureto a scheduler.
 11. The method of claim 1, further comprising setting amodulation control scheme (MCS) for the UE based on the interferencemeasure.
 12. The method of claim 1, wherein the receiving at a wirelesstransceiver comprises receiving at a 2G, 3G, 4G, 5G or Wi-Fi radiotransceiver.
 13. The method of claim 1, further comprising transmittingthe interference measure from a self-organizing network (SON) controllerto a coordination server in an operator core network.